Modelling the biphasic growth of non-starter lactic acid bacteria on starter-lysate as a substrate

Enhancing quality of ruminant feed through fungal treatment: Usage of bamboo shoot residues

In this investigation, we explore the harnessing of bamboo shoot residues (BSR) as a viable source for ruminant feed through fungal treatment, with the overarching objective of elevating feed quality and optimizing bamboo shoot utilization. The white-rot fungi (Wr.fungi), Aspergillus niger (A.niger), and its co-cultures (A.niger&Wr.fungi) were employed to ferment BSR. And the impact of different fermentation methods and culture time on the chemical composition (Crude protein Ash, neutral detergent fibre and acid detergent fibers), enzyme activity (Cellulase, Laccase, Filter paperase and Lignin peroxidase activities), and rumen digestibility in vitro were assessed. The findings reveal a nota ble 30.39% increase in crude protein in fermented BSR, accompanied by respective decreases of 13.02% and 17.31% in acid detergent fiber and neutral detergent fibre content. Enzyme activities experienced augmentation post-fermentation with A.niger&Wr.fungi. Specifically, the peak Cellulase, Laccase, and Lignin peroxidase activities for BSR with Wr.fungi treatment reached 748.4 U/g, 156.92 U/g, and 291.61 U/g, respectively, on the sixth day of fermentation. Concurrently, NH3-N concentration exhibited an upward trend with prolonged fermentation time. Total volatile fatty acids registered a decline, and the Acetate/Propionate ratio reached its nadir after 6 days of fermentation under the A.niger&Wr.fungi treatment. These outcomes furnish a theoretical foundation for the development of ruminant feeds treated via fungal co-culture.

Cyclic pairwise interaction representing a rock-paper-scissors game maintains the population of the vulnerable yeast Saccharomyces cerevisiae within a multispecies sourdough microbiome

IMPORTANCE

Traditionally, multispecies consisting of lactic acid bacteria and yeasts collaboratively engage sourdough fermentation, which determines the quality of the resulting baked goods. Nonetheless, the successive transfer of these microbial communities can result in undesirable community dynamics that prevent the formation of high-quality sourdough bread. Thus, a mechanistic understanding of the community dynamics is fundamental to engineer sourdough complex fermentation. This study describes the population dynamics of five species of lactic acid bacteria-yeast communities in vitro using a generalized Lotka-Volterra model that examines interspecies interactions. A vulnerable yeast species was maintained within up to five species community dynamics by obtaining support with a cyclic interspecies interaction. Metaphorically, it involves a rock-paper-scissors game between two lactic acid bacteria species. Application of the generalized Lotka-Volterra model to real food microbiomes including sourdoughs will increase the reliability of the model prediction and help identify key microbial interactions that drive microbiome dynamics.

Tracking microbial quality, safety and environmental contamination sources in artisanal goat cheesemaking factories

A harmonised microbiological survey was performed in two artisanal factories of raw goat milk cheeses (A and B) located in the Andalusian region (Spain). A total of 165 different control points or samples (raw materials, final products, food-contact surfaces [FCS], and air) were examined as microbial and pathogen sources of contamination of artisanal goat raw milk cheeses. For raw milk samples analysed from both producers, the concentrations of aerobic-mesophilic bacteria (AMB), total coliforms, coagulase-positive Staphylococcus spp. (CPS), lactic-acid bacteria (LAB) and moulds and yeasts ranged between 3.48 and 8.59, 2.45-5.48, 3.42-4.81, 4.99-8.59 and 3.35-6.85 log cfu/mL respectively. For the same microbial groups, the analysis of raw milk cheeses revealed concentrations ranging from 7.82 to 8.88, 2.00-6.82, 2.00-5.28, 8.11-9.57 and 2.00-5.76 log cfu/g, respectively. Although the raw material analysed from producer A presented higher microbial loads and between-batch variability, it was B the producer with the most loaded final products. Regarding the microbial air quality, the fermentation area, storage room, milk reception and packaging room were the most AMB loaded places, while the ripening chamber was the area with higher fungal loads in bioareosol from both producers. Conveyor belts, cutting machine, storage boxes and brine tank were highlighted as the most contaminated FCS evaluated. Staphylococcus aureus was the only pathogen detected within the set of 51 isolates from samples as revealed by MALDI-TOF and molecular PCR, with a prevalence of 12.5% for samples from the producer B. The public health risk attributed to the consumption of artisanal goat cheese should not be neglected, and may consider the whole cheesemaking processing chain, from microbiological quality of raw milk to the ready-to-eat final product, especially concerning the presence of S. aureus.

Computationally efficient framework for diagnosing, understanding and predicting biphasic population growth

Throughout the life sciences, biological populations undergo multiple phases of growth, often referred to as biphasic growth for the commonly encountered situation involving two phases. Biphasic population growth occurs over a massive range of spatial and temporal scales, ranging from microscopic growth of tumours over several days, to decades-long regrowth of corals in coral reefs that can extend for hundreds of kilometres. Different mathematical models and statistical methods are used to diagnose, understand and predict biphasic growth. Common approaches can lead to inaccurate predictions of future growth that may result in inappropriate management and intervention strategies being implemented. Here, we develop a very general computationally efficient framework, based on profile likelihood analysis, for diagnosing, understanding and predicting biphasic population growth. The two key components of the framework are as follows: (i) an efficient method to form approximate confidence intervals for the change point of the growth dynamics and model parameters and (ii) parameter-wise profile predictions that systematically reveal the influence of individual model parameters on predictions. To illustrate our framework we explore real-world case studies across the life sciences.

Growth and Metabolism of Lacticaseibacillus casei and Lactobacillus kefiri Isolated from Qymyz, a Traditional Fermented Central Asian Beverage

The growth characteristics of two strains of lactic acid bacteria (LAB), Lacticaseibacillus casei and Lactobacillus kefiri, isolated from qymyz, a traditional fermented mare milk beverage, were studied and modeled, including the effect of different carbohydrates, pH, and temperature. Along with population, substrates, and metabolites, lactic acid and ethanol were monitored by HPLC. Growth parameters were obtained from mono- and biphasic logistic growth models that fit the population evolution of L. casei and L. kefiri, respectively. The effect of temperature and pH on the growth rate was represented with the gamma concept model, while the effect of the limiting substrate was evaluated according to the Monod equation. Lastly, a simplified Luedeking and Piret equation was used to represent metabolite production. The optimum values of pH and temperature were 6.69 ± 0.20, 38.63 ± 0.32 °C, 5.93 ± 0.08, and 33.15 ± 0.53 °C, with growth rate values of 0.66 ± 0.01 h−1 and 0.29 ± 0.01 h−1 for L. casei and L. kefiri, respectively. L. casei had a homofermentative pathway, while L. kefiri was heterofermentative, with an ethanol production rate of 2.90 × 10−9 mg·CFU−1. The Monod model showed that L. casei had the lowest Ks value for lactose, while for L. kefiri, it was the highest among milk carbohydrates. These results show that the population of the two LAB strains and therefore the concentrations of acid and ethanol can be controlled by the fermentation conditions and that our model can help to significantly improve the production of qymyz.

Properties of an acid-tolerant, persistent Cheddar cheese isolate, Lacticaseibacillus paracasei GCRL163

The distinctive flavours in hard cheeses are attributed largely to the activity of nonstarter lactic acid bacteria (NSLAB) which dominate the cheese matrix during maturation after lactose is consumed. Understanding how different strains of NSLAB survive, compete, and scavenge available nutrients is fundamental to selecting strains as potential adjunct starters which may influence product traits. Three Lacticaseibacillus paracasei isolates which dominated at different stages over 63-week maturation periods of Australian Cheddar cheeses had the same molecular biotype. They shared many phenotypic traits, including salt tolerance, optimum growth temperature, growth on N-acetylglucosamine and N-acetylgalactosamine plus delayed growth on D-ribose, carbon sources likely present in cheese due to bacterial autolysis. However, strains 124 and 163 (later named GCRL163) survived longer at low pH and grew on D-tagatose and D-mannitol, differentiating this phenotype from strain 122. When cultured on growth-limiting lactose (0.2%, wt/vol) in the presence of high concentrations of L-leucine and other amino acids, GCRL163 produced, and subsequently consumed lactate, forming acetic and formic acids, and demonstrated temporal accumulation of intermediates in pyruvate metabolism in long-term cultures. Strain GCRL163 grew in Tween 80-tryptone broths, a trait not shared by all L. casei-group dairy isolates screened in this study. Including citrate in this medium stimulated growth of GCRL163 above citrate alone, suggesting cometabolism of citrate and Tween 80. Proteomic analysis of cytosolic proteins indicated that growth in Tween 80 produced a higher stress state and increased relative abundance of three cell envelope proteinases (CEPs) (including PrtP and Dumpy), amongst over 230 differentially expressed proteins.

Developments in effective use of volatile organic compound analysis to assess flavour formation during cheese ripening

In the burgeoning demand for optimization of cheese production, ascertaining cheese flavour formation during the cheese making process has been the focal point of determining cheese quality. In this research reflection, we have highlighted how valuable volatile organic compound (VOC) analysis has been in assessing contingent cheese flavour compounds arising from non-starter lactic acid bacteria (NSLAB) along with starter lactic acid bacteria (SLAB), and whether VOC analysis associated with other high-throughput data might help provide a better understanding the cheese flavour formation during cheese process. It is widely known that there is a keen interest to merge all omics data to find specific biomarkers and/or to assess aroma formation of cheese. Towards that end, results of VOC analysis have provided valuable insights into the cheese flavour profile. In this review, we are pinpointing the effective use of flavour compound analysis to perceive flavour-forming ability of microbial strains that are convenient for dairy production, intertwining microbiome and metabolome to unveil potential biomarkers that occur during cheese ripening. In doing so, we summarised the functionality and integration of aromatic compound analysis in cheese making and gave reflections on reconsidering what the role of flavour-based analysis might have in the future.

Effect of Lactic Acid Bacteria Strains on the Growth and Aflatoxin Production Potential of Aspergillus parasiticus, and Their Ability to Bind Aflatoxin B1, Ochratoxin A, and Zearalenone in vitro

The increased consumption of plant-based foods has intensified the concern related to mycotoxin intoxication. This study aimed to investigate the effect of selected lactic acid bacteria (LAB) strains on the growth of Aspergillus parasiticus NRRL 2999 and its production of aflatoxin (AF). The ability of the heat-killed (100°C for 1 h) LAB strains to bind aflatoxin M1 (AFM1) in milk and aflatoxin B1 (AFB1), ochratoxin A (OTA), and zearalenone (ZEN) in potassium phosphate buffer (PPB) was also evaluated in vitro. Ten LAB strains were tested individually, by inoculating them simultaneously with the fungus or after incubation of the fungus for 24 or 48 h at 25°C. Double layer yeast extract sucrose (YES) agar, de Man Rogosa and Sharpe (MRS) agar, and YES broth were incubated for 7 days at 25°C to follow the development of the fungus. Levilactobacillus spp. 3QB398 and Levilactobacillus brevis 2QB422 strains were able to delay the growth of A. parasiticus in YES broth, even when these strains were inoculated 24 h after the fungus. The inhibitory effect of these LAB strains was confirmed by the reduction of fungus colony size, suggesting dominance of LAB by competition (a Lotka-Voltera effect). The production of AFB1 by A. parasiticus was inhibited when the fungus was inoculated simultaneously with Lactiplantibacillus plantarum 3QB361 or L. plantarum 3QB350. No AFB1 was found when Levilactobacillus spp. 2QB383 was present, even when the LAB was inoculated 48 h after the fungus. In binding studies, seven inactivated LAB strains were able to promote a reduction of at least 50% the level of AFB1, OTA, and ZEN. This reduction varied depending on the pH of the PPB. In milk, however, only two inactivated LAB strains were able to reduce AFM1, with a reduction of 33 and 45% for Levilactobacillus spp. 3QB398 (Levilactobacillus spp.) and L. brevis 2QB422, respectively. Nevertheless, these results clearly indicate the potential of using LAB for mycotoxin reduction.